library(DNAcopy)
library(foreach)
library(plyr)
library(dplyr)
source("R/CNV_functions_AKS12202017.R")
Introduction
The following code generates figures for the Halobacterium CNV manuscript. This code uses the CNV package DNAcopy to analyze both gene expression and ChIP microarrays.
## All gene expression microarrays (numbers are standardized z scores)
all_data <- read.delim(file = "data/Gene_expression_Master.txt", row.names = 1)
## Empty array to be filled for the generation of segment maps
rarray <- read.delim(file = "data/rarray_allloci.txt")
GE microarray data analysis
The following commented chunk takes a long time to run. A preprocessed object, provided in the github data/ folder, can be loaded instead (see below).
# CNA.ob <- CNA(all_data[,1:1154], all_data$Chr, all_data$Start,data.type = 'logratio', sampleid = colnames(all_data)[1:1154])
# smoothed <- smooth.CNA(CNA.ob)
# segsmot <- segment(smoothed, verbose = 0) ## Set verbose = 1 if number of arrays is not huge
# save(segsmot, file = "data/segmented_GE_arrays.Rdata")
load(file = "data/segmented_GE_arrays.Rdata")
Figure 3 - GE segmentation up vs downregulation on main chromosome
chromosome, 20kb cutoff, Fig 3A

Calcluate functional enrichment in large GE frequency peaks on chromosome, fig 3B
#Find segments present in >= 5% of arrays, determine functional enrichments in chromosome
ge20k.5<-subset(t1f20k.split[[1]], (Thresh_up + Threshdown) >= 58)
#analysis in this code chunk relies upon https://github.com/amyschmid/histone_arCOG. Load source from there.
GE.5percent.arcog<-cogtest2(ge20k.5$GeneName, cogs, 0.05)
write.table (GE.5percent.arcog, file = "data/ge20k_freqpks_5percent_arCOGs.txt", sep = "\t") #Supplementary table?
#Determine which genes are in which arCOG categories, save as supplementary tables
ge20k.5.pk1<-cogset(ge20k.5$GeneName, cogs, "Cell motility ")
write.table (ge20k.5.pk1, file = "ge20k_freqpks_5percent_pk1genes.txt",sep = "\t")
ge20k.5.pk2<-cogset(ge20k.5$GeneName, cogs, "Translation; ribosomal structure and biogenesis ")
write.table (ge20k.5.pk2, file = "ge20k_freqpks_5percent_pk2.txt", sep = "\t")
ge20k.5.pk3<-cogset(ge20k.5$GeneName, cogs, "Coenzyme transport and metabolism ")
write.table (ge20k.5.pk3, file = "ge20k_freqpks_5percent_pk3.txt", sep = "\t")
#similar code was used to calculate enrichments in gene expression data frequency peaks for megaplsmids from t1f20k.split[[2]] and t1f20k.split[[3]] except at 5k threshold.
ChIP microarray data analysis
Samples were parsed, median-centered, scaled, and segmented in independent batches before combining. The following code takes segmented chip array data and creates composite maps.
## Read in segmented ChIP data
test <- read.delim(file = "data/all_clone_fragments_chIP.txt")
## Read in Trmb file 12 for example segmentation output
load(file = "data/trmb12.Rdata")
Example segmentation output, Trmb12 array
shown in Figure 1 example of genomic break point detection in ChIP arrays using DNAcopy
Analyzing: Trmb.12

Table 1: How many CNVs were detected in each array (GE and ChIP data)?
## First we consider GE data. Filter segments by significance across main chromosome.
all.clone.segs.GE<- segsmot$output
all.clone.segs.GE$seg.length <- (all.clone.segs.GE$loc.end - all.clone.segs.GE$loc.start)
segs.GE.20k <- subset (all.clone.segs.GE, seg.length >=20000)
segs.GE.20k <- subset (segs.GE.20k, chrom == "Chr" & (seg.mean >= 1 | seg.mean <= -1))
#for pNRC200
#segs.GE.20k.p200 <- subset (all.clone.segs.GE, seg.length >=20000)
segs.GE.20k.p200 <- subset (segs.GE.20k.p200, chrom == "pNRC200" & (seg.mean >= 1 | seg.mean <= -1))
#for pNRC100
#segs.GE.20k.p100 <- subset (all.clone.segs.GE, seg.length >=20000)
segs.GE.20k.p100 <- subset (segs.GE.20k.p100, chrom == "pNRC100" & (seg.mean >= 1 | seg.mean <= -1))
## Determine how many significant segments were contained within which GE arrays on main chromosome
freq.per.array20 <- plyr:::count(segs.GE.20k, "ID")
hist(freq.per.array20$freq, col = "grey", main = "Distribution of putative CNVs within each GE array", xlab = "Number of arrays")
#for pNRC100
freq.per.array20.p100 <- plyr:::count(segs.GE.20k.p100, "ID")
hist(freq.per.array20.p100$freq, col = "grey", main = "Distribution of putative CNVs within each GE array", xlab = "Number of arrays")
#for pNRC200
freq.per.array20.p200 <- plyr:::count(segs.GE.20k.p200, "ID")
hist(freq.per.array20.p200$freq, col = "grey", main = "Distribution of putative CNVs within each GE array", xlab = "Number of arrays")
## Next we consider chip data. Filter segments by significance at 5k threshold
test$seg.length <- (test$loc.end - test$loc.start)
segs.chip.5k <- subset (test, seg.length >= 5000)
segs.chip.5k <- subset (segs.chip.5k, chrom == "Chr" & (seg.mean >= 0.5 | seg.mean <= -0.5))
## Determine how many significant segments were contained within which ChIP arrays
freq.per.array.chip.5 <- plyr:::count(segs.chip.5k, "ID")
hist(freq.per.array.chip.5$freq, col = "grey", main = "Distribution of putative CNVs within each ChIP array", xlab = "Number of arrays")

Figure 5
Frequency map of all ChIP CNVs, with IS elements marked
sig.per.array<-read.delim ("data/num_signif_segs_per_arrays.txt")
hist(sig.per.array$total.signif.segs.per.array, breaks = 12, col = "grey", xlab = "Number CNVs per array", main = "CNVs are frequent")

Fig 5A: IS elements are detected within CNV regions.
Fig 5B: IS elements are associated with CNV regions at higher rate than expected by chance: bootstrapping results
plotchr_chip2(copymap = chip.split, narrays = 48, ymax = 80, ish_table = ish)
legend('topleft',legend=c('CNV','IS', '10% threshold'),col=c('black',rgb(0.1,0.1,.8,.3), 'red'),cex=1.2,bg='white', lty=c(1,2),lwd=2)
abline(h = 10, col = "red")

#points(x = sample(peaks7, 1000), y = c(rep(2,1000)), col = "green", pch =16, cex= .5)
Appendix
hist(ish.boot, col = "gray", xlim = c(0,15), xlab = "Number of IS elements\n in CNV regions", cex.lab=1.2, breaks =10)
abline( v = 14, lty = 2)

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.
---
title: "Halo_CNV_figure_code_FINAL"
date: "January 19 2018"
editor_options:
  chunk_output_type: inline
output:
  html_notebook: default
  pdf_document: default
authors: Keely Dulmage and Amy Schmid
---


```{r}
library(DNAcopy)
library(foreach)
library(plyr)
library(dplyr)

source("R/CNV_functions_AKS12202017.R")
```



## Introduction

The following code generates figures for the Halobacterium CNV manuscript.  This code uses the CNV package DNAcopy to analyze both gene expression and ChIP microarrays.

```{r}
## All gene expression microarrays (numbers are standardized z scores)
all_data <- read.delim(file = "data/Gene_expression_Master.txt", row.names = 1)

## Empty array to be filled for the generation of segment maps
rarray <- read.delim(file = "data/rarray_allloci.txt")

```



## GE microarray data analysis

The following commented chunk takes a long time to run.  A preprocessed object, provided in the github data/ folder, can be loaded instead (see below).
```{r, message = F}
# CNA.ob <- CNA(all_data[,1:1154], all_data$Chr, all_data$Start,data.type = 'logratio', sampleid = colnames(all_data)[1:1154]) 
# smoothed <- smooth.CNA(CNA.ob)
# segsmot <- segment(smoothed, verbose = 0)  ## Set verbose = 1 if number of arrays is not huge
# save(segsmot, file = "data/segmented_GE_arrays.Rdata")
```
```{r}
load(file = "data/segmented_GE_arrays.Rdata")
```

### Figure 2, frequency map plots for megaplasmids pNRC100 and pNRC200

Generate maps of segments at different fragment size thresholds
```{r}
t1f5k.copy <- copymap4(ref_array = rarray, seg_array = segsmot$output, threshold = 1, f.size = 5000)
t1f10k.copy <- copymap4(ref_array = rarray, seg_array = segsmot$output, threshold = 1, f.size = 10000)
t1f20k.copy <- copymap4(ref_array = rarray, seg_array = segsmot$output, threshold = 1, f.size = 20000)
t1f50k.copy <- copymap4(ref_array = rarray, seg_array = segsmot$output, threshold = 1, f.size = 50000)
t1f100k.copy <- copymap4(ref_array = rarray, seg_array = segsmot$output, threshold = 1, f.size = 100000)
```

Split copy maps by genomic elements
```{r}
t1f5k.split <- split2(t1f5k.copy)
t1f10k.split <- split2(t1f10k.copy)
t1f20k.split <- split2(t1f20k.copy)
t1f50k.split <- split2(t1f50k.copy)
t1f100k.split <- split2(t1f100k.copy)
```

pNRC100 by gene expression segment size frequency, figure 2A left
```{r fig.width = 8, fig.height = 5, echo = F}
plotchr.col(t1f5k.split[[2]],1154,35, 'orange')
add_copyplot(t1f10k.split[[2]],1154,'green')
add_copyplot(t1f20k.split[[2]],1154,'blue')
add_copyplot(t1f50k.split[[2]],1154,'purple')
add_copyplot(t1f100k.split[[2]],1154,'black')
legend('topright', col=c('orange','green','blue','purple','black'), legend=c('5 kb','10 kb', '20 kb','50 kb','100 kb'), lwd=3, bg='white', cex=1.2)
```

pNRC200 by gene expression segment size frequency, figure 2A right
```{r fig.width = 8, fig.height = 5, echo = F}
plotchr.col(t1f5k.split[[3]],1154,10, 'orange')
add_copyplot(t1f10k.split[[3]],1154,'green')
add_copyplot(t1f20k.split[[3]],1154,'blue')
add_copyplot(t1f50k.split[[3]],1154,'purple')
add_copyplot(t1f100k.split[[3]],1154,'black')
#legend('topright', col=c('orange','green','blue','purple','black'), legend=c('5 kb','10 kb', '20 kb','50 kb','100 kb'), lwd=3, bg='white', cex=1.2)
text(175000, 8.2,  cex = 1, font = 2 )
text (325000, 8.2, label = 2, cex = 1, font= 2)
```


pNRC100 up and downregulated segment frequency map, Figure 2B left
```{r fig.width = 5, fig.height = 5, echo = F}
## regions 20kb or larger, threshold of 1 
plotplas.GE2(copymap = t1f20k.split[[2]], narrays = 1154, yrange = c(0,10))
```

pNRC200 up and downregulated segment frequency map, Figure 2B right
```{r fig.width = 8, fig.height = 5, echo = F}
## regions 20kb or larger, threshold of 1 
plotplas.GE2(copymap = t1f20k.split[[3]], narrays = 1154, yrange = c(0,10))
```

### Figure 3 - GE segmentation up vs downregulation on main chromosome

chromosome, 20kb cutoff, Fig 3A
```{r fig.width = 8, fig.height = 5, echo = F}
## regions 20kb or larger, threshold of 1 
plotplas.GE2(copymap = t1f20k.split[[1]], narrays = 1154, yrange = c(0,10))
```

Calcluate functional enrichment in large GE frequency peaks on chromosome, fig 3B
```{r}
#Find segments present in >= 5% of arrays, determine functional enrichments in chromosome
ge20k.5<-subset(t1f20k.split[[1]], (Thresh_up + Threshdown) >= 58)

#cogset and cogtest functions also available via https://github.com/amyschmid/histone_arCOG and Dulmage et al., 2015 mBio.

GE.5percent.arcog<-cogtest2(ge20k.5$GeneName, cogs, 0.05)
write.table (GE.5percent.arcog, file = "data/ge20k_freqpks_5percent_arCOGs.txt", sep = "\t") #Supplementary table?
#Determine which genes are in which arCOG categories, save as supplementary tables 
ge20k.5.pk1<-cogset(ge20k.5$GeneName, cogs, "Cell motility ")
write.table (ge20k.5.pk1, file = "ge20k_freqpks_5percent_pk1genes.txt",sep = "\t")
ge20k.5.pk2<-cogset(ge20k.5$GeneName, cogs, "Translation; ribosomal structure and biogenesis ")
write.table (ge20k.5.pk2, file = "ge20k_freqpks_5percent_pk2.txt", sep = "\t")
ge20k.5.pk3<-cogset(ge20k.5$GeneName, cogs, "Coenzyme transport and metabolism ")
write.table (ge20k.5.pk3, file = "ge20k_freqpks_5percent_pk3.txt", sep = "\t")

#similar code was used to calculate enrichments in gene expression data frequency peaks for megaplsmids from t1f20k.split[[2]] and t1f20k.split[[3]] except at 5k threshold.
```

## ChIP microarray data analysis

Samples were parsed, median-centered, scaled, and segmented in independent batches before combining.  The following code takes segmented chip array data and creates composite maps.
```{r}
## Read in segmented ChIP data 
test <- read.delim(file = "data/all_clone_fragments_chIP.txt")
## Read in Trmb file 12 for example segmentation output
load(file = "data/trmb12.Rdata")
```

### Example segmentation output, Trmb12 array 

shown in Figure 1 example of genomic break point detection in ChIP arrays using DNAcopy
```{r fig.width = 12, fig.height = 5, echo = F}
trmb12.cna <- CNA(genomdat = as.numeric(trmb12.m$Scaled), chrom = trmb12.m$Chr, maploc = as.numeric(trmb12.m$Position), sampleid = "Trmb 12")
trmb12.smooth <- smooth.CNA(trmb12.cna)
trmb12.segsmot <- segment(trmb12.smooth)
copyplot.chr.alt(trmb12.segsmot, c(-2,8))
```



### Figure 4
Segment grequency map of ChIP CNVs across 48 arrays, categorized by depletion and amplification events
```{r}
# Generate copymap
crarray <- read.delim(file = "data/rarray_2400_moved_probes.txt")
crarray <- droplevels(crarray[crarray$Chr == "Chr",])

#5k threshold
chip.copy <- copymap4(ref_array = crarray, seg_array = test, threshold = 0.5, f.size = 5000)
chip.split <- split2(chip.copy)[[1]] %>% dplyr::arrange(Start)

```

#### Figure 4A
Frequency map of all ChIP CNVs, 5k threshold, 10% array threshold, 16 pks marked.
```{r fig.width = 12, fig.height = 5, echo = F}
plotchr(chip.split, 48, 80)
abline (h = 10, col = "red")
pks.16<-read.delim ("data/ChIP_16pks_forR.txt", sep= "\t")
abline (v = pks.16$pk.center, col = "grey")
text((pks.16$pk.center), 70, labels = c(1:16),  cex = 0.8, font = 2 )
```

#### Fig 4B
```{r fig.width = 12, fig.height = 5, echo = F}
plotplas.chip(chip.split, 48, yrange = c(0,80))
#legend('topleft',legend=c('Amplification','Depletion'),col=c('cyan','blue'),cex=0.8,bg='white', lty=c(1,1),lwd=2)
```


### Table 1: How many CNVs were detected in each array (GE and ChIP data)?
```{r}
## First we consider GE data. Filter segments by significance across main chromosome.
all.clone.segs.GE<- segsmot$output
all.clone.segs.GE$seg.length <- (all.clone.segs.GE$loc.end - all.clone.segs.GE$loc.start)
segs.GE.20k <- subset (all.clone.segs.GE, seg.length >=20000)
segs.GE.20k <- subset (segs.GE.20k, chrom == "Chr" & (seg.mean >= 1 | seg.mean <= -1))
#for pNRC200
#segs.GE.20k.p200 <- subset (all.clone.segs.GE, seg.length >=20000)
segs.GE.20k.p200 <- subset (segs.GE.20k.p200, chrom == "pNRC200" & (seg.mean >= 1 | seg.mean <= -1))
#for pNRC100
#segs.GE.20k.p100 <- subset (all.clone.segs.GE, seg.length >=20000)
segs.GE.20k.p100 <- subset (segs.GE.20k.p100, chrom == "pNRC100" & (seg.mean >= 1 | seg.mean <= -1))

## Determine how many significant segments were contained within which GE arrays on main chromosome
freq.per.array20 <- plyr:::count(segs.GE.20k, "ID")
hist(freq.per.array20$freq, col = "grey", main = "Distribution of putative CNVs within each GE array", xlab = "Number of arrays") 

#for pNRC100
freq.per.array20.p100 <- plyr:::count(segs.GE.20k.p100, "ID")
hist(freq.per.array20.p100$freq, col = "grey", main = "Distribution of putative CNVs within each GE array", xlab = "Number of arrays") 

#for pNRC200
freq.per.array20.p200 <- plyr:::count(segs.GE.20k.p200, "ID")
hist(freq.per.array20.p200$freq, col = "grey", main = "Distribution of putative CNVs within each GE array", xlab = "Number of arrays") 

```

```{r}
## Next we consider chip data. Filter segments by significance at 5k threshold
test$seg.length <- (test$loc.end - test$loc.start)
segs.chip.5k <- subset (test, seg.length >= 5000)
segs.chip.5k <- subset (segs.chip.5k, chrom == "Chr" & (seg.mean >= 0.5 | seg.mean <= -0.5))

## Determine how many significant segments were contained within which ChIP arrays 
freq.per.array.chip.5 <- plyr:::count(segs.chip.5k, "ID")
hist(freq.per.array.chip.5$freq, col = "grey", main = "Distribution of putative CNVs within each ChIP array", xlab = "Number of arrays")

```

## Figure 5
Frequency map of all ChIP CNVs, with IS elements marked

```{r}
## read in ISH table
ish <- read.delim(file = "data/20170703_ISfinder_ISH_elements.txt")
## read in peaks vector
peaks <-load("data/Chip_peak_regions.Rdata")
```

Fig 5A: IS elements are detected within CNV regions.
```{r fig.width = 12, fig.height = 5, echo = F}
plotchr_chip2(copymap = chip.split, narrays = 48, ymax = 80, ish_table = ish)
legend('topleft',legend=c('CNV','IS', '10% threshold'),col=c('black',rgb(0.1,0.1,.8,.3), 'red'),cex=1.2,bg='white', lty=c(1,2),lwd=2)
abline(h = 10, col = "red")
#points(x = sample(peaks7, 1000), y = c(rep(2,1000)), col = "green", pch =16, cex= .5)

```


Fig 5B: IS elements are associated with CNV regions at higher rate than expected by chance: bootstrapping results
```{r}
set.seed(8876)
ISboot <- function(IS_number, peaks){
	boot=c()
	for(i in 1:10000){
	ISlist= sample(1:2014239,IS_number)	
 	boot[i]= length(which(ISlist %in% peaks))
	}
	boot
}

## of IS elements in chr peaks from ChIP data (note: IS table is for chromosome only)
is.n <- length(ish$Start[ish$Start %in% peaks7])

ish.boot <- ISboot(is.n, peaks7)

```
```{r fig.width=5, fig.height=4, echo=F}
hist(ish.boot, col = "gray", xlim = c(0,15), xlab = "Number of IS elements\n in CNV regions", cex.lab=1.2, breaks =10)
abline( v = 14, lty = 2)
```


## Appendix
```{r}
sessionInfo()
```


```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```


Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot.
